7 kittens, none well defined. Because the loss function it is optimising taps out once it has got "close" and close for a multiple object prompt is _a lot_ further away than for a single subject prompt (here is the 1 kitten version https://labs.openai.com/s/1aCOUxNT19kbMZZtEBG7CoFY - this is basically witchcraft it is so good, the group shot is a joke).
I suppose you could massively reduce the loss amount you are willing to accept but that doesn't guarantee dalle with optimise the correct part of the pictures - maybe I'd have just ended up with really, really good floors.
The other thing Dalle is bad at is backgrounds, and once again this is due to "optimising an error score". https://labs.openai.com/s/U1Vo2fxThuXmQZzIwLQ4g9Ai nothing about this is right. At a superficial glance it looks like the view over a city but it's a random splatching of building cutouts and when you look at the detail of the builds they are a blur of pixels that kind of approximate doors and windows but are nothing of the sort. They are super fuzzy and dream like. Because it's trying to generate an image that looks like a cityscape from its memory of Glasgow cityscapes. THere's no coherance because it's trying to covert random pixels into a cityscape not for buildings out of components that humans know go to makeup buildings.
I'm not an expert on AI, but your complaints sound like minor versions of the major problems that these image generation AI's had a couple of years ago. It used to be that they could only create a mishmash of textures reminiscent of the subject and style, and struggled creating distinct objects at all.
Now, your examples simply show some slight artifacts and lack of details on specific things. You're presenting remaining shortcomings on these metrics as "fundamental to how it works not a flaw that can be iterated away", when in fact they have mostly been iterated away over the past few years.
Dalle is trying to optimise a bunch of random pixels to meet the prompt.
It has a strong sense of what 1 object is. Ask it for a photo of a kitten and you get an jaw droppingly realistic photo of a kitten.
Ask it for a picture of 6 kittens and you get, well, whatever this is: https://labs.openai.com/s/PIZJe6GCfat9soN3WOV3eC9p
7 kittens, none well defined. Because the loss function it is optimising taps out once it has got "close" and close for a multiple object prompt is _a lot_ further away than for a single subject prompt (here is the 1 kitten version https://labs.openai.com/s/1aCOUxNT19kbMZZtEBG7CoFY - this is basically witchcraft it is so good, the group shot is a joke).
I suppose you could massively reduce the loss amount you are willing to accept but that doesn't guarantee dalle with optimise the correct part of the pictures - maybe I'd have just ended up with really, really good floors.
The other thing Dalle is bad at is backgrounds, and once again this is due to "optimising an error score". https://labs.openai.com/s/U1Vo2fxThuXmQZzIwLQ4g9Ai nothing about this is right. At a superficial glance it looks like the view over a city but it's a random splatching of building cutouts and when you look at the detail of the builds they are a blur of pixels that kind of approximate doors and windows but are nothing of the sort. They are super fuzzy and dream like. Because it's trying to generate an image that looks like a cityscape from its memory of Glasgow cityscapes. THere's no coherance because it's trying to covert random pixels into a cityscape not for buildings out of components that humans know go to makeup buildings.
I'm not an expert on AI, but your complaints sound like minor versions of the major problems that these image generation AI's had a couple of years ago. It used to be that they could only create a mishmash of textures reminiscent of the subject and style, and struggled creating distinct objects at all.
Now, your examples simply show some slight artifacts and lack of details on specific things. You're presenting remaining shortcomings on these metrics as "fundamental to how it works not a flaw that can be iterated away", when in fact they have mostly been iterated away over the past few years.
Dalle doesn't produce any better images of people than "This Person Does Not Exist". All that's happened is it has a large corpus.
A larger corpus allows it to be more varied but it doesn't fix the fundamental limitations.
Getting 7 things when I ask for 6 is not a minor artefact!
If you ranked its training data by similarity to your "witchcraft" images, it wouldnt seem witchraft.
Recall that it's stored a compressed version of TBs of images.
Sure, it _seems_ like withcraft. The illusion disappears when you know how it is done.